Characterizing Resident Space Objects from Photometric Signatures (CROPS)

Award Information
Agency:
Department of Defense
Branch:
Air Force
Amount:
$149,992.00
Award Year:
2014
Program:
SBIR
Phase:
Phase I
Contract:
FA9453-14-M-0153
Agency Tracking Number:
F141-123-0544
Solicitation Year:
2014
Solicitation Topic Code:
AF141-123
Solicitation Number:
2014.1
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, 02138-
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
115243701
Principal Investigator
 Joe Gorman
 Principal Software Engineer
 (617) 491-3474
 jgorman@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
N/A
Abstract
The US is highly dependent on space resources for communications and imaging, as well as positioning, navigation, and timing services that support military operations, government operations, and commercial interests. Because the space environment is both congested and contested, effectively operating space resources is a challenge. The Joint Space Operations Center requires high-quality space situational awareness to protect our free access to space. Currently, resident space objects are characterized primarily based on astrometry measurements, while photometric object resolution techniques are underutilized in SSA systems, such as JMS/ARCADE. By analyzing photometric signatures, we can advance the state of the art in deep space object resolution because certain features which can be inferred from a photometric signature cannot be effectively calculated using astrometry. These features can be used to resolve observations of deep space objects, either with astrometric data or based solely on photometric analysis. Charles River Analytics proposes to develop a service for Characterizing Resident Space Objects from Photometric Signatures, (CROPS). CROPS will introduce valuable techniques for the interpretation and application of photometric data, which has previously been underused in the characterization of RSOs in real-time, operational processes.

* information listed above is at the time of submission.

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